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Sample Customer Clusters Q5 Division, LLC 1. Overview Used to describe the work that Q5 Division, LLC did for the client and what will be discussed in.

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Presentation on theme: "Sample Customer Clusters Q5 Division, LLC 1. Overview Used to describe the work that Q5 Division, LLC did for the client and what will be discussed in."— Presentation transcript:

1 Sample Customer Clusters Q5 Division, LLC 1

2 Overview Used to describe the work that Q5 Division, LLC did for the client and what will be discussed in the cluster report. 2

3 Overall Cluster Distributions and Penetration Customers Prospects 3 Penetration The Customer Clusters divide the current customers into relatively uniform size segments of people. The prospects within the areas where the stores are located are not quite as uniform with significantly less people in clusters 7, 8 and 10 and more people in 3,4,and 6. This difference in distribution allows us to see how well example 1 is penetrating the population for each cluster. Example 1 is penetrating cluster 7 significantly more than any other cluster. This signifies that example 1 has a very strong appeal to individuals in this cluster. There is also a high penetration in clusters 8,10,5 and 1, but to a lesser degree. At this time, Sample appears to have challenges attracting people in clusters 3, 4 and 6. Example 1 is attracting only it’s fair share of all of the other clusters (2, 9 and 11).

4 Value Distribution Across Clusters 1.Cluster 5 is made up individuals with the highest customer value for people with Activity A only and the second highest Activity A and Activity B combined activity. 2.Cluster 3 is made up individuals with the highest customer value for people with Activity B only and the first highest Activity A and Activity B combined activity. 3.Clusters 8 and 10 are made up individuals with the lowest customer value for people with Activity A only and Activity A and Activity B combined activity. 4.Clusters 2 and 10 are made up of individuals with the lowest customer value for people with Activity B only. 4 1 1 1 1 2 2 3 3 3 3 4 4 2 2 FileMatchCluster Customers % of Customers Act A & Act B Combined Total Value (M) % of Act A & Act B Combined Value Act. A & Act. B Combined Average Value 164,9623.94%$92.37%$139 2112,2166.81%$174.36%$148 371,3344.33%$164.19%$223 474,2354.50%$154.04%$207 559,4123.60%$153.85%$247 667,5804.10%$133.30%$186 761,9173.76%$133.34%$205 893,9065.70%$102.52%$102 979,8714.85%$143.63%$173 1093,0105.64%$102.52%$103 1172,9074.42%$133.48%$182 851,35051.66%$14337.59%$168 124,4031.48%$20.61%$96 260,4533.67%$51.32%$83 342,8942.60%$71.88%$167 446,1802.80%$61.56%$128 545,5632.76%$51.42%$119 639,6212.40%$51.19%$115 739,0242.37%$41.14%$111 849,9103.03%$51.25%$95 935,3632.15%$41.12%$121 1042,7612.59%$30.86%$76 1149,8713.03%$61.50%$115 476,04328.88%$5313.86%$111 125,5671.55%$133.48%$518 241,3812.51%$215.49%$505 322,0781.34%$194.91%$845 426,1941.59%$184.81%$699 523,4491.42%$194.94%$801 623,2991.41%$143.59%$586 726,2751.59%$184.68%$678 839,1112.37%$143.79%$368 929,6301.80%$184.71%$605 1038,7872.35%$153.95%$387 1124,9681.51%$164.22%$644 320,73919.46%$18548.56%$576 1,648,132100.00%$381100.00%$231 c. Pawn and Retail Total Grand Total a. Activity A Only a. Pawn Only Total b. Activity B Only b. Retail Only Total c. Act. A & Act. B

5 Cluster Prioritization Summary 5

6 Descriptive Statistics Activity A Transactions 6 Activity B Transactions Who is in Cluster 1? They are low income single females. They represent 7.7% of the customers and 5 % of prospects. They make a very low income but are doing what they can to build a nest egg. They don’t tend to be very active as it relates to credit card usage. They are a bit more likely than average to do X than Y if they are Activity A customers. If they are Activity B customers, they are less likely than average to do X. Strategic Assessment: Example 1 is attracting these individuals at a higher rate than average, but they are generally not high value customers for Activity A or Activity B. We need to be very strategic and targeted in the way we communicate and market to them. Activity A Vs. Activity B Cluster 1

7 Descriptive Statistics Activity A Transactions 7 Activity B Transactions Who is in Cluster 2? They are big families that are very responsive to mail. They represent 14% of the customers and 13% of prospects. They have a lot of credit activity in the way of credit card usage. They are more than likely living in Ohio and Tennessee. They are participating in Activity A and buying everything at a rate that is very proportionate to the averages for the customer base. Strategic Assessment: Example 1 is attracting these individuals at a slightly higher rate than average, but they are generally not high value customers for Activity A or Activity B. This group could become a money pit if we are not incredibly strategic and targeted in the way we communicate and market to them. Activity A Vs. Activity B Cluster 2

8 Descriptive Statistics Activity A Transactions 8 Activity B Transactions Who is in Cluster 3? Cluster 3 are couples with adult children living at home. They tend to be early adopters and have incomes that are significantly higher than their peers. They represent 7.8% of the customers and 21% of prospects. They have a lot of credit activity in the way of credit card usage. They are more than likely living in Texas. They are more likely than average to be participating in Activity A and buying firearms and musical instruments. Strategic Assessment Example 1 is attracting these individuals at a rate that is significantly lower than average, but they are generally very high value customers for Activity A or Activity B. This group has tremendous potential but the prospect pool is so large that it is critical to leverage Example 1 customer clone models and Activity B customer clone models to target the people with the highest likelihood to be interested in becoming an Example 1 customer. Activity A Vs. Activity B Cluster 3

9 Descriptive Statistics Activity A Transactions 9 Activity B Transactions Who is in Cluster 4? They are older couples that are very traditional and tend to be offline. They have built up a positive nest egg on a very moderate income. They represent 7.8% of the customers and 11% of prospects. They have a lot of credit activity in the way of credit card usage. They are more than likely to be living in Tennessee. They are more likely than average to be participating in Activity A and buying firearms and musical instruments. Strategic Assessment: Example 1 is attracting these individuals at a rate that is significantly lower than average, but they are generally very high value customers for Activity A and Activity B. This group has tremendous potential but the prospect pool is so large that it is critical to leverage Example 1 customer clone models and Activity B customer clone models to target the people with the highest likelihood to be interested in becoming a Example 1 customer. Activity A Vs. Activity B Cluster 4

10 Descriptive Statistics Activity A Transactions 10 Activity B Transactions Who is in Cluster 5? They are large Hispanic Catholic families with a significant amount of debt. They live in small homes and have lived where they are for many years. They make up 7.3% of the customers and 5% of prospects. They have a lot of credit activity in the way of credit card usage. They are more than likely to be living in Texas. They are more likely than average to be participating in Activity A and buying everything. Strategic Assessment: Example 1 is attracting these individuals at a rate that is significantly higher than average and they are generally very high value customers for Activity A and Activity B. This group has tremendous potential. It represents one of two high priority clusters. Although it is recommended that we test targeting models for this cluster, creating programs for this group as a whole should be relatively low risk. Activity A Vs. Activity B Cluster 5

11 Descriptive Statistics Activity A Transactions 11 Activity B Transactions Who is in Cluster 6? These are senior singles that are very conservative. They opt for debit cards with rewards programs over credit cards. They make up 8.1% of the customers and 16% of prospects. They are more likely than average to be participating in Activity A. They are more likely than average to be buying firearms, musical instruments, sporting goods and tools. Strategic Assessment: Example 1 is attracting these individuals at a rate that is a bit lower than average and they are average value customers for Activity A and Activity B. This group has potential if we are very targeted with who we market to and what we market to them. It is a cluster that has the greatest need for predictive models for targeting profitably and success-ability. Activity A Vs. Activity B Cluster 6

12 Descriptive Statistics Activity A Transactions 12 Activity B Transactions Who is in Cluster 7? They are young Hispanic individuals making a modest income. They make up 9.4% of the customers and 2% of prospects. They have less than average credit activity and credit card usage. They are more than likely to be living in Texas. They are more likely than average to be pawning jewelry, cameras, binoculars and telescopes and buying everything but firearms. Strategic Assessment: Example 1 is attracting these individuals at a rate that is significantly higher than average and they are generally very good value customers for Activity A and Activity B. This group has tremendous potential. It represents one of two high priority clusters. Although it is recommended that we test targeting models for this cluster, creating programs for this group as a whole should be relatively low risk. Activity A Vs. Activity B Cluster 7

13 Descriptive Statistics Activity A Transactions 13 Activity B Transactions Who is in Cluster 8? These are high mobility, tech savvy, single males. They represent 11.8% of the customers and 5 % of prospects. They are making a very modest income, have contributed very little to savings thus far, and have little to no credit activity. They are living everywhere but are less likely than average to be living in Texas. They are participating in Activity A and Activity B. Strategic Assessment: Example 1 is attracting these individuals at a higher rate than average, but they are generally very low value customers for Activity A and Activity B. We need to be very strategic and targeted in the way we communicate and market to them. We should consider suppressing this group from programs until we are ready to test in a targeted manner to potentially reduce the volume of low value traffi. Activity A Vs. Activity B Cluster 8

14 Descriptive Statistics Activity A Transactions 14 Activity B Transactions Who is in Cluster 9? These are middle aged single women making modest incomes. They are likely to be living in suburbia. They have lower than average credit activity. They make up 9.8% of the customers and 8% of prospects. They are more likely than average to be participating in Activity A, everything but firearms, musical instruments, sporting goods or tools. They are more likely than average to be buying jewelry. Strategic Assessment: Example 1 is attracting these individuals at a rate that is a bit higher than average and they are average value customers for pawn and retail. This group has potential if we are very targeted with who we market to and what we market to them. It is a cluster that has the greatest need for predictive models for targeting profitably and successfully. The fact that they are buying jewelry and they are single women infers a high potential marketing campaign to this group for jewelry sales: They are probably buying it for themselves They probably can’t afford to pay full retail based on their income They probably don’t have someone to buy it for them Activity A Vs. Activity B Cluster 9

15 Descriptive Statistics Activity A Transactions 15 Activity B Transactions Who is in Cluster 10? These are the youngest people on the customer base. They are couples with kids and single moms barely making ends meet and just getting by day to day. They represent 8.3% of the customers and 5% of prospects. They are making a very low income, have contributed very little to savings thus far, and have lower than average credit activity. They are living everywhere but are more likely than average to be living in Ohio. They are most likely participating in Activity A and buying electronics. Strategic Assessment: Example 1 is attracting these individuals at a higher rate than average, but they are generally very low value customers for Activity A Vs. Activity B. We need to be very strategic and targeted in the way we communicate and market to them. We should consider suppressing this group from programs until we are ready to test in a targeted manner to potentially reduce the volume of low value traffic in the stores. Activity A Vs. Activity B Cluster 10

16 Descriptive Statistics Activity A Transactions 16 Activity B Transactions Who is in Cluster 11? These are families with children living in suburbia. They make an income that is 50% more than the average household and have a net worth that is 49% higher than average. They have much higher than average credit activity. They make up 8.2% of the customers and 9% of prospects They are more likely than average to be buying everything but jewelry. Strategic Assessment: Example 1 is attracting these individuals at a rate that is a bit lower than average and they are average value customers for Activity A and Activity B. This group has potential if we are very targeted with who we market to and what we market to them. It is a cluster that has the greatest need for predictive models for targeting profitably and successfully. Activity A Vs. Activity B Cluster 11

17 Initial Marketing Strategy Matrix This matrix can be used when creating marketing programs. For example, if you want to create a program that would increase email capture or move people to an online channel you would start with clusters 3, 8, 10 and 11 because they tend to be more hi tech oriented. If you want to create a program to Hispanic individuals, you would use clusters 5 and 7. 17

18 Next Steps Finish up POC model(s) for one cluster to determine the value of modeling by cluster. Finish up the example 1 cluster analysis. 18

19 19 Thank you


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